# coding:utf-8
from collections import deque
import numpy as np
import time
# import imutils
import cv2

# 设定红色阈值，HSV空间
redLower = np.array([170, 100, 100])
redUpper = np.array([179, 255, 255])
# 初始化追踪点的列表
mybuffer = 16
pts = deque(maxlen=mybuffer)
counter = 0
# 打开摄像头
camera = cv2.VideoCapture(0)
# 等待两秒
time.sleep(3)
# 遍历每一帧，检测红色识别物体
while True:
    # 读取帧
    (ret, frame) = camera.read()
    # 判断是否成功打开摄像头
    if not ret:
        print
        'No Camera'
        break
    # frame = imutils.resize(frame, width=600)
    # 转到HSV空间
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    # 根据阈值构建掩膜
    mask = cv2.inRange(hsv, redLower, redUpper)
    # 腐蚀操作
    mask = cv2.erode(mask, None, iterations=2)
    # 膨胀操作，其实先腐蚀再膨胀的效果是开运算，去除噪点
    mask = cv2.dilate(mask, None, iterations=2)
    cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]
    # 初始化识别物体圆形轮廓质心
    center = None
    # 如果存在轮廓
    if len(cnts) > 0:
        # 找到面积最大的轮廓
        c = max(cnts, key=cv2.contourArea)
        # 确定面积最大的轮廓的外接圆
        ((x, y), radius) = cv2.minEnclosingCircle(c)
        # 计算轮廓的矩
        M = cv2.moments(c)
        # 计算质心
        center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))
        # 只有当半径大于10时，才执行画图
        if radius > 10:
            cv2.circle(frame, (int(x), int(y)), int(radius), (0, 255, 255), 2)
            cv2.circle(frame, center, 5, (0, 0, 255), -1)
            # 把质心添加到pts中，并且是添加到列表左侧
            pts.appendleft(center)
    else:  # 如果图像中没有检测到识别物体，则清空pts，图像上不显示轨迹。
        pts.clear()

    for i in range(1, len(pts)):
        if pts[i - 1] is None or pts[i] is None:
            continue
        # 计算所画小线段的粗细
        thickness = int(np.sqrt(mybuffer / float(i + 1)) * 2.5)
        # 画出小线段
        cv2.line(frame, pts[i - 1], pts[i], (0, 0, 255), thickness)
        # 判断移动方向
        if counter >= 10 and i == 1 and len(pts) >= 10:
            dX = pts[-10][0] - pts[i][0]
            dY = pts[-10][1] - pts[i][1]
            (dirX, dirY) = ("", "")
            """
            if np.abs(dX) > 20:
                dirX = "Left" if np.sign(dX) == 1 else "Right"

            if np.abs(dY) > 20:
                dirY = "Down" if np.sign(dY) == 1 else "Up"

            if dirX != "" and dirY != "":
                direction = "{}-{}".format(dirY, dirX)
            else:
                direction = dirX if dirX != "" else dirY

            cv2.putText(frame, direction, (20, 50), cv2.FONT_HERSHEY_SIMPLEX, 2,
                        (0, 255, 0), 3)
            cv2.putText(frame, "dx: {}, dy: {}".format(dX, dY), (10, frame.shape[0] - 10),
                        cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
            """
    cv2.imshow('Frame', frame)
    # 键盘检测，检测到esc键退出
    k = cv2.waitKey(1) & 0xFF
    counter += 1
    if k == 27:
        break
# 摄像头释放
camera.release()
# 销毁所有窗口
cv2.destroyAllWindows()
